Applications for signal processing are broad and continue to increase. Examples of signal processing applications include transmission and reception of messages by mobile devices, speech recognition, and clock signals used to time internal operations of CPUs and GPUs.
Signals may be composed of multiple frequencies. The lowest frequency that makes up part of a signal is known as the fundamental frequency of the signal. Signals may also include unwanted components, known as noise. The presence of noise in a signal may reduce signal performance in an application. A noisy signal may transmit erroneous or incomplete information. Noise may have particular characteristics which can be thought of as a signature. For example, noise may be characterized as low frequency or high frequency. Low frequency noise may be noise that occurs at a frequency lower than the fundamental frequency of a signal. High frequency noise, then, may be all noise other than low frequency noise. Detecting and analyzing a noise signature may allow the source of the noise to be determined, eliminated and/or reduced.